Presenting empirical equations for estimating Manning roughness coefficient in furrow irrigation in different irrigation phases

Document Type : Research Paper

Authors

Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

Abstract

 
This study aimed to estimation of the Manning roughness coefficient (n) in different phases and events of irrigation using empirical relations. For this purpose, six inflow rates in two flow categories, low and high, three consecutive irrigation events, advance and storage phases, two irrigation intervals and two types of soil texture were investigated. Next, the correlation between roughness and these parameters was investigated using Pearson and Kendall statistical tests. Then, using its results, regression equations were developed to estimate Manning’s n in different irrigation phases. The results indicated that the advance time and the size of clods before irrigation had a high correlation and the slope, initial soil moisture and the size of clods after irrigation had a low correlation with the Manning’s n data in the whole irrigation event. The roughness coefficient of the advance phase also had the highest correlation with the advance time. The highest and lowest correlation coefficients between the parameters and roughness coefficient of the storage phase were related to advance time and inflow rate with values of 0.65 and -0.31, respectively, which shows high correlation and direct relationship between advance time and roughness and weak correlation and inverse relationship between flow rate and roughness. The average values of R2, RMSE, and NRMSE indices in the provided relationships were 0.87, 0.014, and 26.97%, respectively, which indicated the appropriate accuracy of these relationships. Finally, it was suggested to conduct similar studies in different field and hydraulic conditions so that the presented relations are more comprehensive and can be recommended in other fields since the development of such relations can increase the speed of roughness estimation in different phases and the ease of using it.

Keywords

Main Subjects


Presenting empirical equations for estimating Manning roughness coefficient in furrow irrigation in different irrigation phases

EXTENDED ABSTRACT

Introduction

Manning equation is an empirical equation that is commonly used to calculate water flow in open channels. However, its application in investigating the flow hydraulics in surface irrigation, especially in irrigation furrows, faces limitations due to the assumptions made for it. These limitations have led the researchers to consider Manning roughness coefficient as a fixed number during each irrigation event by accepting possible errors in the estimation and to pay less attention to its changes during an irrigation event. This is despite the fact that if the value of Manning roughness coefficient is estimated more (less) than the actual value, considering that the roughness is a force resisting the flow, the flow rate is estimated less (more) than the actual value and leads to many errors in the simulation and hence, it is necessary to pay more attention to the time changes of the roughness coefficient by using various methods and assumptions that lead to the simplification of roughness estimation complexities.

Objectives/Goals:

This research aimed to developing regression equations to estimate roughness in different irrigation phases, using different hydraulic and non-hydraulic parameters.

Research Method

To investigate the values of Manning roughness coefficient in different phases and events in furrow irrigation, different treatments were considered in such a way as to cover most of the factors influencing roughness. For this purpose, six inflow rates in two flow categories, low (with an average of 0.27 liters per second) and high (with an average of 0.54 liters per second), three consecutive irrigation events, advance and storage phases, two irrigation intervals (5 and 10 days) and two types of soil texture were investigated. Secondly, Manning roughness coefficient was determined in whole irrigation event, advance and storage phases and respectively by using SIPAR_ID model, Manning equation and WinSRFR. Finally, the mutual effect of various hydraulic and non-hydraulic parameters on Manning roughness coefficient was investigated and regression equations based on the influential parameters were developed using SPSS software to estimate the roughness coefficient in different phases.

Results

The results showed that Manning roughness coefficient in the advance, storage phases and whole irrigation event in the first to third irrigations ranged between 0.017 and 0.636, 0.015 and 0.317, and 0.015 and 0.34, respectively. The average was 0.083, 0.054 and 0.055. The results also showed that the advance time and the size of clods before irrigation had a high correlation and the slope, moisture and the size of clods after irrigation had a low correlation with the Manning roughness coefficient data in the entire irrigation event. The roughness coefficient of the advance phase also had the highest correlation with the advance time. The highest and lowest correlation coefficients between the parameters and roughness coefficient of the storage phase were related to the advance time and inflow rate with values of 0.65 and -0.31, which shows high correlation and direct relationship between advance time and weak correlation and inverse relationship between flow rate and roughness.

Conclusion

Results indicate the suitable accuracy of the methods used to estimate the roughness coefficient even in the advance phase where the application of Manning equation can be considered more than before.

The sensitivity analysis of Manning roughness coefficient in the equations developed to estimate roughness in different phases also showed that the cross-sectional area and flow rate (inflow, outflow and average) had the greatest influence on Manning roughness coefficient in all irrigation phases, and the recession and advance time were other parameters influencing the roughness coefficient. The importance and mutual influence of flow and cross-section is clear and has been given much attention.

As results indicate, it is very important to take into account the mutual relationship between roughness and advance and recession time, since as an example, the increase of roughness coefficient in the furrow is due to various reasons such as the presence of clods, Obstruction in the furrow path, irregularity in the path (irregular plowing) etc. can lead to an increase in the advance time and as a result an excessive increase in depth infiltration and consequently water loss or an imbalance in the distribution of water along the furrow, which may have received less attention so far and might require more precision.

Abbasi, F. (2012) Principles of flow in surface irrigation. National Irrigation and Drainage Committee (in Persian).
Abbasi, Fariborz and Ebrahimian, Hamed. (1402). Surface irrigation hydraulics. University publications Center (in Persian).
Adamala, S., Raghuwanshi, N. S., & Mishra, A. (2014). Development of Surface Irrigation Systems Design and Evaluation Software (SIDES). Computers and Electronics in Agriculture, 100, 100–109. https://doi.org/10.1016/j.compag.2013.11.004
Amiri, M. J., Bahrami, M., Hamidifar, H., & Eslamian, S. (2016). Modification of furrow Manning’s roughness coefficient estimation by finite difference technique under surge and continuous flow. International Journal of Hydrology Science and Technology, 6(3), 226. https://doi.org/10.1504/IJHST.2016.077390
Arjamand, M., Farmani Kharajo, F., Rezaei, M., Razavifar, R. and Kazemi Mutal, A. (2017). Sensitivity analysis of Manning equation parameters of open hydraulic channels using differential equations. Elite Journal of Engineering Sciences, 3(3), 107-111 (in Persian).
Baradaran, R. (2010). Investigating the effect of land preparation operations on soil hydrodynamic coefficient in furrow irrigation. Shahid Chamran University of Ahwaz (in Persian).
Bautista, E., Clemmens, A. J., & Strelkoff, T. S. (2009). Structured Application of the Two-Point Method for the Estimation of Infiltration Parameters in Surface Irrigation. Journal of Irrigation and Drainage Engineering, 135(5), 566–578. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000054
Bautista, E., Clemmens, A. J., Strelkoff, T. S., & Schlegel, J. (2009). Modern analysis of surface irrigation systems with WinSRFR. Agricultural Water Management, 96(7), 1146–1154. https://doi.org/10.1016/j.agwat.2009.03.007
Behzad Izadi, & W. W. Wallender. (1985). Furrow Hydraulic Characteristics and Infiltration. Transactions of the ASAE, 28(6), 1901–1908. https://doi.org/10.13031/2013.32539
Burguete, J., Lacasta, A., & García-Navarro, P. (2014). SURCOS: A software tool to simulate irrigation and fertigation in isolated furrows and furrow networks. Computers and Electronics in Agriculture, 103, 91–103. https://doi.org/10.1016/j.compag.2014.02.004
Clemmens, A. J. (2009). Errors in surface irrigation evaluation from incorrect model assumptions. Journal of Irrigation and Drainage Engineering, 135(5), 556–565. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000059
Clemmens, A. J., Eisenhauer, D. E., & Maheshwari, B. L. (2001). Infiltration and Roughness Equations for Surface Irrigation: How Form Influences Estimation. An ASAE Meeting Presentation No. 01-2255, 0300(xx), 1–19.
Dewedar, O. M., Mehanna, H. M., & El-shafie, A. F. (2019). Validation of WinSRFR for some hydraulic parameters of furrow irrigation in Egypt. Plant Archives, 19(2), 2108–2115.
Ebrahimian, H. (2014). Soil infiltration characteristics in alternate and conventional furrow irrigation using different estimation methods. KSCE Journal of Civil Engineering, 18(6), 1904–1911. https://doi.org/10.1007/s12205-014-1343-z
Enciso-Medina, J., Martin, D., & Eisenhauer, D. (1998). Infiltration Model for Furrow Irrigation. Journal of Irrigation and Drainage Engineering, 124(2), 73–80. https://doi.org/10.1061/(ASCE)0733-9437(1998)124:2(73)
Esfandiari, M., & Maheshwari, B. L. (1998). Suitability of Selected Flow Equations and Variation of Manning’s n in Furrow Irrigation. Journal of Irrigation and Drainage Engineering, 124(2), 89–95. https://doi.org/10.1061/(ASCE)0733-9437(1998)124:2(89)
Etedali, H. R., Ebrahimian, H., Abbasi, F., & Liaghat, A. (2011). Evaluating models for the estimation of furrow irrigation. 9(2), 641–649.
Gill, M. A. (1976). EXACT SOLUTION OF GRADUALLY VARIED FLOW. Journal of the Hydraulics Division, 102(9), 1353–1364. https://doi.org/10.1061/JYCEAJ.0004617/REFERENCES
Gillies, M. H., & Smith, R. J. (2015). SISCO: surface irrigation simulation, calibration and optimisation. Irrigation Science, 33(5), 339–355. https://doi.org/10.1007/s00271-015-0470-8
GiMey, J. E., Kottwitz, E. R., & Wieman, G. a. (1991). Roughness Coefficients for Selected Residue Materials. Journal of Irrigation and Drainage Engineering, 117(4), 503–514. https://doi.org/10.1061/(ASCE)0733-9437(1991)117:4(503)
Jamieson, P. D., Porter, J. R., & Wilson, D. R. (1991). A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field Crops Research, 27(4), 337–350. https://doi.org/10.1016/0378-4290(91)90040-3
Jurriens, M., Zerihun, D., Boonstra, J., & Feyen, J. (2001). SURDEV: Surface Irrigation Software. Design, Operation, and Evaluation of Basin, Border, and Furrow Irrigation. International Institute for Land Reclamation and Improvement.
Kamali, P., Ebrahimian, H., & Parsinejad, M. (2018). Estimation of Manning roughness coefficient for vegetated furrows. Irrigation Science, 36(6), 339–348. https://doi.org/10.1007/s00271-018-0593-9
Kassem, M. A., & Ghonimy, M. I. (2011). Determination of manning roughness coefficient for border irrigation system. 28(April), 302–323.
Katopodes, N. D., Tang, J., & Clemmens, A. J. (1990). Estimation of Surface Irrigation Parameters. Journal of Irrigation and Drainage Engineering, 116(5), 676–696. https://doi.org/10.1061/(ASCE)0733-9437(1990)116:5(676)
Li, Z., & Zhang, J. (2001). Calculation of Field Manning’ s Roughness Coefficient. Agricultural Water Management, 49, 153–161.
Maheshwari, B. L. (1992). Suitability of different flow equations and hydraulic resistance parameters for flows in surface irrigation: A review. Water Resources Research, 28(8), 2059–2066. https://doi.org/10.1029/92WR00424
Maheshwari, B. L., & McMahon, T. A. (1992). Modeling Shallow Overland Flow in Surface Irrigation. Journal of Irrigation and Drainage Engineering, 118(2), 201–217.
Mailapalli, D. R., Raghuwanshi, N. S., Singh, R., Schmitz, G. H., & Lennartz, F. (2008). Spatial and Temporal Variation of Manning’s Roughness Coefficient in Furrow Irrigation. Journal of Irrigation and Drainage Engineering, 134(2), 185–192. https://doi.org/10.1061/(ASCE)0733-9437(2008)134:2(185)
Mazarei, R., Soltani Mohammadi, A., Ebrahimian, H., & Naseri, A. A. (2021). Temporal variability of infiltration and roughness coefficients and furrow irrigation performance under different inflow rates. Agricultural Water Management, 245, 106465. https://doi.org/10.1016/j.agwat.2020.106465
Mehri, A., Mohammadi, A. S., Ebrahimian, H., & Boroomandnasab, S. (2023). Evaluation and optimization of surge and alternate furrow irrigation performance in maize fields using the WinSRFR software. Agricultural Water Management, 276, 108052. https://doi.org/10.1016/j.agwat.2022.108052
Mwendera, E. J., & Feyen, J. (1992). Estimation of depression storage and Manning’s resistance coefficient from random roughness measurements. Geoderma, 52(3–4), 235–250. https://doi.org/10.1016/0016-7061(92)90039-A
Nematollahi, B., & Abedini, M. J. (2020). Analytical Solution of Gradually Varied Flow Equation in Non-prismatic Channels. Iranian Journal of Science and Technology - Transactions of Civil Engineering, 44(1), 251–258. https://doi.org/10.1007/s40996-019-00316-5
Nie, W. B., Fei, L. J., & Ma, X. Y. (2014a). Applied closed-end furrow irrigation optimized design based on field and simulated advance data. Journal of Agricultural Science and Technology, 16(2), 395–408.
Nie, W. B., Fei, L. J., & Ma, X. Y. (2014b). Applied closed-end furrow irrigation optimized design based on field and simulated advance data. Journal of Agricultural Science and Technology, 16(2), 395–408.
Nie, W.-B., Li, Y.-B., Zhang, F., Dong, S.-X., Wang, H., & Ma, X.-Y. (2018). A Method for Determining the Discharge of Closed-End Furrow Irrigation Based on the Representative Value of Manning’s Roughness and Field Mean Infiltration Parameters Estimated Using the PTF at Regional Scale. Water, 10(12), 1825. https://doi.org/10.3390/w10121825
Pallant, J. (2010). SPSS Survival Manual. In McGraw-Hill Education (4th ed.).
Pradhan, A., & Khatua, K. K. (2018). Assessment of Roughness Coefficient for Meandering Compound Channels. KSCE Journal of Civil Engineering, 22(5), 2010–2022. https://doi.org/10.1007/s12205-017-1818-9
Ramesh, A., & Ostad‑Ali‑Askari, K. (2023). Effect of effluent and magnetized effluent on Manning roughness coefficient in furrow irrigation. Applied Water Science, 13(1), 1–10. https://doi.org/10.1007/s13201-022-01818-w
Ramezani Etedali, H., Ebrahimian, H., Abbasi, F., & Liaghat, A. (2011). Evaluating models for the estimation of furrow irrigation infiltration and roughness. Spanish Journal of Agricultural Research, 9(2), 641. https://doi.org/10.5424/sjar/20110902-342-10
Ramezani Etedali, H., Liaghat, A., & Abbasi, F. (2012). Evaluation of The EVALUE Model for Estimating Manning’s Roughness in Furrow Irrigation. Irrigation and Drainage, 61(3), 410–415. https://doi.org/10.1002/ird.650
Ramezani, H., Liaqat, A., and Abbasi, F. (2009). Evaluation of EVALUE model to estimate the manning roughness coefficient in furrow irrigation. Journal of Agricultural Engineering Research, 10(3), 83–94 (in Persian).
Rezaei Rad, H., Ebrahimian, H., & Liaqat, A. (2021). Inverse Estimation of Manning Roughness Coefficient Using WinSRFR Model and Investigating Its Variations in Different Irrigation Events. Iranian Journal of Irrigation and Drainage, 3(15), 598-610 (in Persian).
Rezaei Rad, H., Ebrahimian, H., Liaqat, A., Khalji, F., and Shabani Arani, M. (2021). Effect of inflow rate and initial soil moisture on Manning roughness coefficient in advance and storage phases in furrow irrigation. Water and Irrigation Management, 11(2), 159–172. https://doi.org/10.22059/jwim.2021.316828.852 (in Persian).
 Salahou, M. K., Jiao, X., & Lü, H. (2018). Border irrigation performance with distance-based cut-off. Agricultural Water Management, 201(2016), 27–37. https://doi.org/10.1016/j.agwat.2018.01.014
Sedaghatdoost, A., & Ebrahimian, H. (2015). Calibration of infiltration, roughness and longitudinal dispersivity coefficients in furrow fertigation using inverse modelling with a genetic algorithm. Biosystems Engineering, 136, 129–139. https://doi.org/10.1016/j.biosystemseng.2015.05.011
Sepaskhah, A. R., & Bondar, H. (2002). Estimation of Manning Roughness Coefficient for Bare and Vegetated Furrow Irrigation. Biosystems Engineering, 82(3), 351–357. https://doi.org/10.1006/bioe.2002.0076
Seyedzadeh, A., Panahi, A., Maroufpoor, E., & Singh, V. P. (2019). Development of an analytical method for estimating Manning’s coefficient of roughness for border irrigation. Irrigation Science, 37(4), 523–531. https://doi.org/10.1007/s00271-019-00631-9
Smith, R. J., Uddin, M. J., & Gillies, M. H. (2018). Estimating irrigation duration for high performance furrow irrigation on cracking clay soils. Agricultural Water Management, 206, 78–85. https://doi.org/10.1016/j.agwat.2018.03.014
Srivastava, R. (2003). Discussion of ‘“Integrating Equation of Gradually Varied Flow.”’ JOURNAL OF HYDRAULIC ENGINEERING, January, 77–78.
Tabatabaei, S. M., & Asadi, R. (2015). Estimation of Infiltration Parameters and Manning Roughness with SIPAR_ID Software. International Journal of Life Sciences, 9(5), 70–74.
Walker, W. R. (1987). surface irrigation theory and practice (1st ed.).
Walker, W. R. (2003). SIRMOD III Surface Irrigation Simulation, Evaluation and Design Guide and Technical Documentation. Utah State University.
Walker, W. R. (2005). Multilevel Calibration of Furrow Infiltration and Roughness. Journal of Irrigation and Drainage Engineering, 131(2), 129–136. https://doi.org/10.1061/(ASCE)0733-9437(2005)131:2(129)
Xu, J., Cai, H., Saddique, Q., Wang, X., Li, L., Ma, C., & Lu, Y. (2019). Evaluation and optimization of border irrigation in different irrigation seasons based on temporal variation of infiltration and roughness. Agricultural Water Management, 214(23), 64–77. https://doi.org/10.1016/j.agwat.2019.01.003
Yousefi, K. and Banjad, H. (2012). Analyzing the sensitivity of Manning's formula to the roughness coefficient with the method of differential equations. The first national conference on the challenges of water resources and agriculture. https://civilica.com/doc/537966 (in Persian).
Zarekani, K., Ramezani Mederani, H., and Daneshkar Araste, P. (2018). Estimation of infiltration parameters and Manning roughness coefficient under two continuous and cutback flows regimes. Journal of Soil and Water Resources Conservation, 9(2), 89–101 (in Persian).